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Details: https://spacy.io/models/mk#mk_core_news_md
Macedonian pipeline optimized for CPU. Components: tok2vec, morphologizer, parser, senter, ner, attribute_ruler, lemmatizer.
| Feature | Description |
|---|---|
| Name | mk_core_news_md
|
| Version | 3.2.0
|
| spaCy | >=3.2.0,<3.3.0
|
| Default Pipeline | morphologizer, parser, attribute_ruler, lemmatizer, ner
|
| Components | morphologizer, parser, senter, attribute_ruler, lemmatizer, ner
|
| Vectors | 274587 keys, 20000 unique vectors (300 dimensions) |
| Sources | Macedonian Corpus (Damjan Zlatinov, Melanija Gerasimovska, Borijan Georgievski, Marija Todosovska) Macedonian Corpus (Damjan Zlatinov, Melanija Gerasimovska, Borijan Georgievski, Marija Todosovska) Macedonian Corpus (Damjan Zlatinov, Melanija Gerasimovska, Borijan Georgievski, Marija Todosovska) spaCy lookups data (Explosion) Explosion fastText Vectors (cbow, OSCAR Common Crawl + Wikipedia) (Explosion) |
| License | CC BY-SA 4.0
|
| Author | Explosion |
| Model size | 44 MB |
Label Scheme
View label scheme (55 labels for 4 components)
| Component | Labels |
|---|---|
morphologizer
| POS=PROPN, POS=AUX, POS=ADJ, POS=NOUN, POS=ADP, POS=PUNCT, POS=CONJ, POS=NUM, POS=VERB, POS=PRON, POS=ADV, POS=SCONJ, POS=PART, POS=SYM, POS=X, _, POS=INTJ
|
parser
| ROOT, advmod, att, aux, cc, dep, det, dobj, iobj, neg, nsubj, pobj, poss, pozm, pozv, prep, punct, relcl
|
senter
| I, S
|
ner
| CARDINAL, DATE, EVENT, FAC, GPE, LANGUAGE, LAW, LOC, MONEY, NORP, ORDINAL, ORG, PERCENT, PERSON, PRODUCT, QUANTITY, TIME, WORK_OF_ART
|
Accuracy
| Type | Score |
|---|---|
TOKEN_ACC
| 100.00 |
TOKEN_P
| 100.00 |
TOKEN_R
| 100.00 |
TOKEN_F
| 100.00 |
SENTS_P
| 81.25 |
SENTS_R
| 67.53 |
SENTS_F
| 73.76 |
DEP_UAS
| 70.07 |
DEP_LAS
| 53.19 |
ENTS_P
| 76.43 |
ENTS_R
| 74.81 |
ENTS_F
| 75.61 |
POS_ACC
| 93.07 |
Installation
pip install spacy
python -m spacy download mk_core_news_md